This a study on the function of the endocrine glands initiated during embryonal development in vertebrates, which arose in tie with investigations of the role of endocrine factors in the metamorphosis of the Amphibia. investigators have attempted, after the first experiments of Gudernatsch (1909-12) on this problem at the middle of the year 1930 gave a prove on the morphogenetic behaviour of endocrine action on the process of larval development of Amphibia.
If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.
Evidence that there is no correlation.
They can be positive correlation, negative correlation or no correlation depending on 'line of best fit'
Yes it can be a correlation coefficient.
No, it cannot be a correlation coefficient.
Auto correlation is the correlation of one signal with itself. Cross correlation is the correlation of one signal with a different signal.
positive correlation-negative correlation and no correlation
No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).
The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).
If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.
Evidence that there is no correlation.
Indentation rhymes with correlation
No.
No. The units of the two variables in a correlation will not change the value of the correlation coefficient.
No, The correlation can not be over 1. An example of a strong correlation would be .99
They can be positive correlation, negative correlation or no correlation depending on 'line of best fit'
partial correlation is the relation between two variable after controlling for other variables and multiple correlation is correlation between dependent and group of independent variables.